94 research outputs found

    Impaired Autonomic Responses to Emotional Stimuli in Autoimmune Limbic Encephalitis

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    Limbic encephalitis (LE) is an autoimmune-mediated disorder that affects structures of the limbic system, in particular the amygdala. The amygdala constitutes a brain area substantial for processing of emotional, especially fear-related signals. The amygdala is also involved in neuroendocrine and autonomic functions, including skin conductance responses (SCRs) to emotionally arousing stimuli. This study investigates behavioral and autonomic responses to discrete emotion-evoking and neutral film clips in a patient suffering from LE associated with contactin-associated protein-2 (CASPR2)-antibodies as compared to a healthy control group. Results show a lack of SCRs in the patient while watching the film clips, with significant differences compared to healthy controls in the case of fear-inducing videos. There was no comparable impairment in behavioral data (emotion report, valence and arousal ratings). The results point to a defective modulation of sympathetic responses during emotional stimulation in patients with LE, probably due to impaired functioning of the amygdala

    Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: an inter-laboratory study.

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    Antimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial-susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a 'one-stop' test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants, and identify problem cases and factors that lead to discordant results. We produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ('participants') were provided these sequence data without any other contextual information. Each participant used their choice of pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime. We found participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results, but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment, a different antibiotic would have been recommended for each isolate by at least one participant. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases, full recommendations on sequence data quality and standardization in the comparisons between genotype and resistance phenotypes will all play a fundamental role in the successful implementation of AST prediction using WGS in clinical microbiology laboratories

    The emergence and diversification of a zoonotic pathogen from within the microbiota of intensively farmed pigs

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    The expansion and intensification of livestock production is predicted to promote the emergence of pathogens. As pathogens sometimes jump between species, this can affect the health of humans as well as livestock. Here, we investigate how livestock microbiota can act as a source of these emerging pathogens through analysis of Streptococcus suis, a ubiquitous component of the respiratory microbiota of pigs that is also a major cause of disease on pig farms and an important zoonotic pathogen. Combining molecular dating, phylogeography, and comparative genomic analyses of a large collection of isolates, we find that several pathogenic lineages of S. suis emerged in the 19th and 20th centuries, during an early period of growth in pig farming. These lineages have since spread between countries and continents, mirroring trade in live pigs. They are distinguished by the presence of three genomic islands with putative roles in metabolism and cell adhesion, and an ongoing reduction in genome size, which may reflect their recent shift to a more pathogenic ecology. Reconstructions of the evolutionary histories of these islands reveal constraints on pathogen emergence that could inform control strategies, with pathogenic lineages consistently emerging from one subpopulation of S. suis and acquiring genes through horizontal transfer from other pathogenic lineages. These results shed light on the capacity of the microbiota to rapidly evolve to exploit changes in their host population and suggest that the impact of changes in farming on the pathogenicity and zoonotic potential of S. suis is yet to be fully realized.This work was primarily funded by an EU Horizon 2020 grant “PIGSs” (727966) and a ZELS BBSRC award “Myanmar Pigs Partnership (MPP)” (BB/L018934/1). G.G.R.M., E.L.M., and L.A.W. were supported by a Sir Henry Dale Fellowship to L.A.W. jointly funded by the Wellcome Trust and the Royal Society (109385/Z/15/Z). N.H. was supported by a Challenge grant from the Royal Society (CH16011) and an Isaac Newton Trust Research Grant [17.24(u)]. G.G.R.M. was also supported by a Research Fellowship at Newnham College. S.B. is supported by the Medical Research Council (MR/V032836/1). PIC North America provided part of the funds for the sequencing of the isolates from the USA. A.J.B. and M.M. were funded by Medical Research Council and Biotechnology and Biological Sciences Research Council studentships respectively, and M.M. was co-funded by the Raymond and Beverly Sackler Fund. We would like to acknowledge Susanna Williamson at the APHA for providing samples, Oscar Cabezón for sampling of the wild boar population in Spain, Mark O’Dea for access to sequence data from Australian isolates, the PIGSs and MPP consortiums for providing samples and helpful discussions, Julian Parkhill and John Welch for helpful discussions, and two anonymous reviewers for their valuable suggestions for improving the manuscript. This research was funded in whole or in part by the Wellcome Trust. For the purpose of Open Access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript (AAM) version arising from this submission.info:eu-repo/semantics/publishedVersio

    Neuro-cognitive mechanisms of conscious and unconscious visual perception: From a plethora of phenomena to general principles

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    Psychological and neuroscience approaches have promoted much progress in elucidating the cognitive and neural mechanisms that underlie phenomenal visual awareness during the last decades. In this article, we provide an overview of the latest research investigating important phenomena in conscious and unconscious vision. We identify general principles to characterize conscious and unconscious visual perception, which may serve as important building blocks for a unified model to explain the plethora of findings. We argue that in particular the integration of principles from both conscious and unconscious vision is advantageous and provides critical constraints for developing adequate theoretical models. Based on the principles identified in our review, we outline essential components of a unified model of conscious and unconscious visual perception. We propose that awareness refers to consolidated visual representations, which are accessible to the entire brain and therefore globally available. However, visual awareness not only depends on consolidation within the visual system, but is additionally the result of a post-sensory gating process, which is mediated by higher-level cognitive control mechanisms. We further propose that amplification of visual representations by attentional sensitization is not exclusive to the domain of conscious perception, but also applies to visual stimuli, which remain unconscious. Conscious and unconscious processing modes are highly interdependent with influences in both directions. We therefore argue that exactly this interdependence renders a unified model of conscious and unconscious visual perception valuable. Computational modeling jointly with focused experimental research could lead to a better understanding of the plethora of empirical phenomena in consciousness research

    Tackling antibiotic resistance: the environmental framework

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    Antibiotic resistance is a threat to human and animal health worldwide, and key measures are required to reduce the risks posed by antibiotic resistance genes that occur in the environment. These measures include the identification of critical points of control, the development of reliable surveillance and risk assessment procedures, and the implementation of technological solutions that can prevent environmental contamination with antibiotic resistant bacteria and genes. In this Opinion article, we discuss the main knowledge gaps, the future research needs and the policy and management options that should be prioritized to tackle antibiotic resistance in the environment
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